@DanKornas: If machine learning only clicks when you build the pieces yourself, this is a useful repo to keep around. Build your ow…

If machine learning only clicks when you build the pieces yourself, this is a useful repo to keep around. Build your own X - Machine Learning is a public build-from-scratch machine learning tutorial index for learners and builders who want implementation practice. It helps you move from reading algorithms to coding them by organizing ML topics into categories and linking several NumPy examples for core algorithms. Key features: • Build-from-scratch roadmap – starts at linear/logistic regression and KNN, then expands into deep learning and LLM topics • Core Python examples – includes NumPy code for regression, KNN, loss functions, and activation functions • Category navigation – groups ideas across recommendation systems, computer vision, NLP, forecasting, anomaly detection, and more • Implementation-first learning – matches the README’s goal of building ML pieces from scratch • Ongoing tutorial list – README says it will keep adding new tutorials It’s open-source (Apache-2.0 license). Link in the reply